The research started by developing and evaluating control software for the latest generation of Silicon Carbide (SiC) based traction converters. In paper A, the focus was to determine the optimal switching frequency for SiC based traction inverters in terms of electricity consumption. In paper B, the SiC based inverters were tested on a demo train in Stockholm subway and results from noise tests were included in the optimization. In paper C, different pulse patterns and switching frequencies were evaluated in terms of motor and inverters losses as well as radiated electromagnetic noise.
The forthcoming research will focus on how machine learning methods can be used in the control software to further improve the performance of the traction system.